Mobile communications device with electronic nose

ABSTRACT

Systems and methods for a mobile electronic system that gathers and analyzes odors, airborne chemicals and/or compounds. The system includes a sample delivery component that can gather airborne substances and/or gaseous substances. A detection component can detect the presences of chemicals, substances, and/or visual gases in a sample. Analyzed samples can be compared with known substance and/or odor analysis. In addition, the source of the sample can be determined. Accordingly, odor, gas, and/or airborne substance identification can be accomplished.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. Non-Provisional applicationSer. No. 17/539,589 filed Dec. 1, 2021 and entitled “MOBILECOMMUNICATIONS DEVICE WITH ELECTRONIC NOSE,” which is a continuation ofU.S. Non-provisional application Ser. No. 16/875,453 filed May 15, 2020(now U.S. Pat. No. 11,215,595) and entitled “MOBILE COMMUNICATIONSDEVICE WITH ELECTRONIC NOSE”, which is a continuation of U.S.Non-provisional application Ser. No. 16/290,330 filed Mar. 1, 2019 (nowU.S. Pat. No. 10,697,948) and entitled “MOBILE COMMUNICATIONS DEVICEWITH ELECTRONIC NOSE”, which is a continuation of U.S. Non-provisionalapplication Ser. No. 15/460,124 filed Mar. 15, 2017 (now U.S. Pat. No.10,254,260) and entitled “MOBILE COMMUNICATIONS DEVICE WITH ELECTRONICNOSE”, which is a continuation of U.S. Non-provisional application Ser.No. 13/839,206 filed Mar. 15, 2013 (now U.S. Pat. No. 9,645,127) andentitled “ELECTRONIC NOSE SYSTEM AND METHOD”, which claims priority toU.S. Provisional Application Ser. No. 61/643,781 filed May 7, 2012 andentitled “ELECTRONIC NOSE SYSTEM AND METHOD”; the entireties of eachapplication are incorporated herein by reference.

TECHNICAL FIELD

This disclosure relates to detection of chemical compounds, gases, andodor. More particularly to methods and systems for detection ofchemicals or gases in air samples through a portable handheld device.

BACKGROUND

The proliferation, advancement, and affordability of electroniccomputing devices such as smart phones, laptop computers, personalcomputers, digital cameras, tablets, personal digital assistants (PDAs)and other electronic devices has made powerful electronic devices moreavailable to the general public than ever before. Advancements indetection devices capable of odor detection, chemical detection and gasdetection have made some detection devices common place in homes. Forexample, a sensor that can indicate presence of a chemical, gas orsubstance of interest can be useful to identify an unacceptable level ofa toxic or explosive gas. There is an unmet need by the state of the artfor convenient, rapid and reliable identification or detection ofchemicals, gases, compounds, substances and the like.

SUMMARY

The following presents a simplified summary of the specification inorder to provide a basic understanding of some aspects of thespecification. This summary is not an extensive overview of thespecification. It is intended to neither identify key or criticalelements of the specification nor delineate the scope of any particularimplementations of the specification, or any scope of the claims. Itspurpose is to present some concepts of the specification in a simplifiedform as a prelude to the more detailed description that is presented inthis disclosure.

Systems and methods disclosed herein relate to detection of odors,chemicals and gasses via handheld electronic devices (e.g., mobilephone). A sample delivery component is coupled to an electronicprocessor. The sample delivery component collects a headspace of asample. The headspace is a portion of the sample that is to be analyzed.The sample delivery component can passively and/or actively collect theheadspace of a sample by drawing air, for example.

A detection component is coupled to the electronic processor and sampledelivery component. The detection component can analyze the headspace.The headspace analysis can determine presence and ratio of chemical,physical, and/or visual substances the make-up the headspace. Aspects ofthe detection component and the electronic processor can be coupled to acomputer readable memory. The memory can store known analyzed samples ofchemicals, gases, and/or odors, e.g., in the form of digital signatures,hash values, or any suitable use of identifying indicia orrepresentation. The detection component can compare the analyzedheadspace to known analyzed samples in the memory to determine thesource of the headspace (e.g., flower, foodstuff, alcohol, perfume,etc.) and/or associate the analyzed headspace with a known source. Inanother example, when an analyzed headspace is determined to be a newcombination of odors, gases, and/or chemicals, then the new combinationof odors, gases, and/or chemicals can be stored in the memory.

In another embodiment, the detection component can determine if theheadspace is a visual gas such as smoke without comparing the headspaceto samples stored in memory. In this embodiment, the detection componentcan visually analyze the headspace.

In another embodiment, an image detection component (e.g., camera) cancapture an image of a source of the headspace. The detection componentcan receive the captured image and determine the source of the headspacevia analysis of the captured image, the analyzed headspace, or acombination thereof.

A display component displays can display a result of the analyzedheadspace. The result can be a known source (e.g., type of flower, typeof perfume, etc.). The result can comprise text and/or image. In oneexample, a result can be saved in memory and associated with as a newodor, gas, or chemical source.

The following description and the drawings set forth certainillustrative aspects of the specification. These aspects are indicative,however, of but a few of the various ways in which the principles of thespecification may be employed. Other advantages and novel features ofthe specification will become apparent from the following detaileddescription of the specification when considered in conjunction with thedrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

Numerous aspects, implementations, and advantages of the presentinvention will be apparent upon consideration of the following detaileddescription, taken in conjunction with the accompanying drawings, inwhich like reference characters refer to like parts throughout, and inwhich:

FIG. 1 illustrates a high-level functional block diagram of an examplemobile electronic nose device;

FIG. 2 illustrates a high-level functional block diagram of an examplemobile electronic nose device including an input component and an outputcomponent;

FIG. 3 illustrates a high-level functional block diagram of an examplemobile electronic nose device in communication with a server;

FIG. 4 illustrates a high-level functional block diagram of an examplesample delivery component;

FIG. 5 illustrates an example schematic diagram of a sample deliverycomponent;

FIG. 6 illustrates a schematic diagram of an external view of examplemobile electronic nose device;

FIG. 7 illustrates an example methodology for gathering and analyzing asample;

FIG. 8 illustrates an example methodology for gathering and analyzing asample including receiving input and analyzing a sample with thereceived input;

FIG. 9 illustrates an example methodology for determining a source of asample including connecting to a server;

FIG. 10 illustrates a high-level functional block diagram of an examplemobile electronic nose device;

FIG. 11 illustrates an example schematic block diagram of a computingenvironment in accordance with this specification; and

FIG. 12 illustrates an example block diagram of a computer operable toexecute various implementations described herein.

DETAILED DESCRIPTION

Various aspects or features of this disclosure are described withreference to the drawings, wherein like reference numerals are used torefer to like elements throughout. In this specification, numerousspecific details are set forth in order to provide a thoroughunderstanding of this disclosure. It should be understood, however, thatcertain aspects of disclosure may be practiced without these specificdetails, or with other methods, components, materials, etc. In otherinstances, well-known structures and devices are shown in block diagramform to facilitate describing this disclosure.

Systems and methods disclosed herein relate to detection of odors,chemicals and/or gasses via handheld electronic devices. In oneimplementation, a mobile device receives, determines and identifies asource of a headspace of a sample. The mobile device is an electroniccomputing device such as for example a smartphone, tablet, PDA, laptop,cookware with circuitry, cooking utensils with circuitry, and the like.

In one embodiment, the mobile device passively receives a sample such aschemicals, gas, or odors. The sample can be received through openings ina body of the mobile device. In another embodiment, a mobile deviceactively draws in the sample via a sample delivery component. The sampledelivery component can include an intake device such as a fan (e.g.,bladed fan, air foil fan and the like), or a manually powered pump, forexample. The intake device can pull air from outside the mobile devicecreating a positive pressure inside the device relative to the outsidepressure. This causes air to pass through the device.

A detection component, coupled to a memory and a CPU, of the mobiledevice can receive a sample of the air. The detection component cananalyze a headspace (portion) of the sample. The detection component candetect presence and amount of chemicals in the headspace. In oneimplementation, the detection component can include a sensory array. Thesensory array can react to various chemicals within the headspace. Thereaction can cause a change in physical or electrical properties of thesensory array. In one example, absorption of the chemicals in theheadspace causes physical alterations of the various sensors in thesensory array. Each sensory array can react differently to the variouschemicals. A CPU can transform the reactions of the sensory array into adigital signal. The digital signal can be computed based on astatistical model. For example, in one non-limiting embodiment, anorganic ultra-thin transistor chemical sensor having a channel thatconsists of one or a few monolayers can be employed. The organic thinfilm transistor chemical sensors can have nearly monolayer thin filmchannels that act as highly-sensitive detectors of trace levels oforganic vapors and can perform quantitative vapor analysis. The organicultra-thin film can be permeable to a chemical analyte of interest.

A memory can store digital signals associated with sources (e.g., arose, a foodstuff, burning foodstuff, etc.). In one embodiment, thedetection component compares the digital signal associated with theheadspace to the stored digital signals within the memory. The detectioncomponent can then find the best match and determine the source of theheadspace. In another embodiment, the mobile device can compare thedigital signal associated with the headspace to a memory of a server,such as a server connected via cellular communication networks,intranet, internet or similar communication networks known in the art.

In another example, the detection component can determine that a bestmatched sample is not in memory. In this case, a new source isassociated with the digital signal associated to the headspace. An inputcomponent can receive information about the source. The memory can storethe associated source with the digital signal.

In another example, the mobile device can receive a plurality ofheadspaces associated with the same sample via the sample deliverycomponent. The detection component can normalize the plurality ofheadspaces into a normalized headspace. The normalized headspace can beanalyzed as above.

In another embodiment, input component can receive information about asource of a sample. In one example, the information can include text,location information (via global positioning satellites, user input,wireless access points, wired access points, etc.), audio information,and/or image information. The detection component can analyze thereceived information and the headspace to determine the source of thesample. In one implementation, the information received by the inputcomponent can narrow the possible sources to be associated with theheadspace to be of a certain genus or type. For example, a voicecapturing device can receive audio and determine that the audio containsa phrase such as “identify this flower”. Thus, the detection componentnarrows the possible sources to flowers.

In another implementation, the detection component can detect if a foodsubstance is expired, not expired, or the quality. For example, thedetection component can determine if milk or wine has gone bad bycomparing an analyzed headspace's associated digital signal to a knowndigital signal. In one aspect, input information can be received as textor audio information such as “is this wine spoiled?” and the detectioncomponent can reduce the amount of digital signals to compare to ananalyzed headspace's digital signal.

In one example, the input component can include an image capturingdevice (e.g., a camera) can capture an image of a source associated witha sample and send the image to the detection component. The detectioncomponent analyzed the image of the source and the headspace of thesample associated with the source. The determination of the source canbe enhanced and/or speed-up through the dual analysis of the capturedimage and the headspace. As one example, the captured image can narrowthe possible sources of the headspace. For example, a sample of thefragrance of a flower can be received and an image of the flower can becaptured. The detection component can determine the headspace isassociated with a flower via analysis of the image of the flower.

Some non-limiting examples of types of sensors or detectors that can beemployed in connection with identification of samples include: acalorimeter, a conductivity sensor, an enzymatic sensor, a biosensor, achemical sensor, an Enzyme-Linked Assay sensor (e.g., an Enzyme-LinkedImmunosorbent Assay (ELISA) sensor), an infrared (IR) spectroscopysensor, a Nuclear Magnetic Resonance (NMR) sensor, an optical sensor, apermittivity sensor, a gas sensor, a Radio Frequency (RF) sensor, anelectronic tongue sensor, a multi-frequency RF sensor, a cantileversensor, an acoustic wave sensor, a piezoelectric sensor, a responsivepolymer-based sensor, a quartz microbalance sensor, a metal oxidesensor, an X-ray Fluorescence (XRF) sensor, a nucleic acid-based sensor(e.g., a DNA-, RNA-, or aptamer-based sensor), or a regenerable sensor.

Furthermore, it is to be appreciated that multiple modalities can beemployed in connection with converging on identification of a sample.For example, image or video capture components of a mobile device can beemployed to identify item(s) of interest to be analyzed, audio analysis,voice analysis, text, can be employed in connection with determiningidentification goals of a user as well as determining properties ofitems that are analyzed. A user can take an image of an item (e.g., asnack) and utter is this allergen safe? The image can be analyzed (e.g.,using pattern recognition) to identify that it is a cookie as well aslikely type of cookie (e.g., peanut butter). Based on the utterance, thesystem determines that the user is interested in ensuring that thecookie does not include items that may cause an allergic reaction (e.g.,nut allergy). The electronic nose can be employed to detect presence ofnuts in the cookie or any other potential allergen that might affect theuser. Accordingly, the combination of pattern, voice and smell detectioncan provide a higher confidence level regarding item and goaldetermination as compared to using just one sensing modality.

Moreover, geographic location, time of day, season, etc. can also beemployed in connection with facilitating identification. For example, aglobal positioning system (GPS) component of the mobile device canprovide geographic location, and such information coupled with temporalor season information can facilitate factoring likelihood of gases,chemicals, substances, compounds, allergens or the like that have a highor low probability of presence at such location and time. If the mobiledevice is located in Ohio during the month of May, likelihood of certainallergens (e.g., tree and grass pollens) can be factored into adetermination of presence of certain items of interest. Likewise, if themobile device is located in the Arctic Circle, and the device is locatedoutside the likelihood of a live plant or animal being a source of anitem is relatively low. In yet another example, identification oflocation within a particular restaurant can also be employed tofacilitate item identification. If the restaurant is an Indianrestaurant as compared to a steak house, the presence of certain exoticspices (e.g., turmeric, saffron, garam masala, cumin, coriander, etc.)is likely to be higher than in the steak house.

Embodiments disclosed herein can leverage multiple modalities (e.g.,image or pattern recognition, location based services, web-based searchtools, electronic noses, chemical sensors, audio recognition, time,date, season, location, etc.) to facilitate converging on user itemidentification goals as well as item identification.

Sensors can be self-cleaning (e.g., vibration, light, chemical or gaswashes, etc.) as well as disposable.

In the smelling process of the human olfactory system, the initial stepis to bind specific odorants to the olfactory receptor protein whichtriggers signal transduction in a cell. Olfactory receptors expressed inthe cell membranes of olfactory receptor neurons are responsible for thedetection of odorant molecules. That is, when the odorants bind to theolfactory receptors as described above, the receptors are activated. Theactivated olfactory receptors are the initial player in a signaltransduction cascade which ultimately produces a nerve impulse which istransmitted to the brain. These olfactory receptors are members of theclass A rhodopsin-like family of G protein-coupled receptors (GPCRs). Inaccordance with an embodiment, an olfactory receptor-functionalizedtransistor is provided, that is useful for a bioelectronic nose whichcan detect and analyze specific odorants with high selectivity, byfunctionalizing a nanostructure transistor with an olfactory receptor(e.g., a lipid membrane having an olfactory receptor protein is formedto cover surfaces of a source electrode, a drain electrode, and ananostructure).

The olfactory receptor protein belongs to a family of G-protein coupledreceptors and may exist over the surface of, the interior of, or thesurface and interior of a lipid double membrane. An olfactory receptormembrane generally includes an ionizable cysteine residue and exists ina conformational equilibrium between biophysically activated andnon-activated states. The activated and non-activated states of theolfactory receptor molecule are associated with a negatively-chargedbase form and a neutral acid form of cysteine, respectively. Whenspecific odorants bind to olfactory receptor molecules, equilibrium ofreceptor molecules moves to an activated receptor form having negativecharges. The negative charges of the olfactory receptor molecules whichwere changed into an activated state modulate contact resistance betweenmetal electrode and nanostructure, leading to reduction in conductance.In accordance with an embodiment, odorant molecules can be detectedhighly selectively based on electrostatic perturbation of ananostructure junction generated from a conformational change by bindingodorants to olfactory receptor molecules. Thus, highly-specificdetection of odorants with femtomolar sensitivity can be achieved inreal time, and various and novel applications such as a highly selectiveartificial nose application can be achieved. In one embodiment, thenanostructure may be at least one form selected from the groupconsisting of nanotube, nanowire, nanorod, nanoribbon, nanofilm, andnanoball. For example, semiconductor nanowires such as siliconnanowires, and carbon nanotubes may be used, and a single-walled carbonnanotube can provide desirable high biocompatibility and devicecharacteristics.

In another embodiment, a random network of single-walled carbonnanotubes (SWCNTs) coated with non-polar small organic molecules inconjunction with learning and pattern recognition algorithms (e.g.,artificial neural networks, multi-layer perception (MLP), generalizedregression neural network (GRNN), fuzzy inference systems (FIS),self-organizing map (SOM), radial bias function (RBF), geneticalgorithms (GAS), neuro-fuzzy systems (NFS), adaptive resonance theory(ART) and statistical methods including, but not limited to, principalcomponent analysis (PCA), partial least squares (PLS), multiple linearregression (MLR), principal component regression (PCR), discriminantfunction analysis (DFA) including linear discriminant analysis (LDA),and cluster analysis including nearest neighbor) can be employed. Forexample, detection of volatile compounds as biomarkers for diagnosis ofmedical conditions can be performed using olfactometry systems thatperform odor detection through use of an array of cross-reactive sensorsin conjunction with pattern recognition algorithms. Each sensor can bewidely responsive to a variety of odorants. Each analyte can produce adistinct signature from an array of broadly cross-reactive sensors. Thisconfiguration allows to considerably widen the variety of compounds towhich a given matrix is sensitive, to increase degree of componentidentification and, in specific cases, to perform an analysis ofindividual components in complex multi-component mixtures. Patternrecognition algorithms can then be applied to the entire set of signals,obtained concurrently from a set (e.g., one or more) of sensors in thearray, in order to glean information on identity, properties andconcentration of vapor exposed to the sensor array.

Referring now to FIG. 1 , there is illustrated a non-limiting exemplaryimplementation of a mobile device 110 in accordance with various aspectsof this disclosure. The mobile device 110 includes a sample deliverycomponent 111, a detection component 120, a computer processing unit(CPU) 130, and a memory 140. The mobile device 110 provides forgathering samples, and detecting and identifying source of a sample. Themobile device 110 receives sample 116 associated with a source 114.Sample 116 can be an odor, chemical, and/or airborne fragrance given offby source 114. In one aspect, CPU 130 is capable of executing variouscomponents and/or portions of components stored in a computer readablememory 140.

The sample delivery component 111 can receive the sample 116. In oneimplementation, the sample delivery component 111 passively receives thesample 116 as the sample 116 diffuses. In another implementation, thesample delivery component 111 actively gathers the sample 116. Forexample, sample delivery component 111 can comprise an intake componentthat draws air into the mobile device 110 or a portion of the mobiledevice by creating a negative air pressure in the mobile device 110 orthe portion of the mobile device relative to an external air pressure.

The sample delivery component 111 is in fluid communication with thedetection component 120. Detection component 120 can receive the sample116 and analyze a headspace of the sample 116. Detection component 120can analyze the chemical composition of the headspace or analyze avisual aspect of the headspace.

In one implementation, detection component 120 includes a sensory array.The sensory array can comprise an array of polymer films, each polymerfilm of the array of polymer films can be of a slightly different type.However, it is to be appreciated that various polymer films of the arrayof polymer films may be of a same type. The electrical conductivity ofthe different types of films varies in the presence of differentchemicals, so that when the array of films is exposed to a particularodor, the different films respond in a characteristic way.

In another example, the sensory array can comprise an array oftransistors made out of various semiconductor materials (e.g., siliconoxide sensor). Transistors made of different materials can responddifferently to different chemicals, so that the array produces adistinctive signal when exposed to an odor.

In another implementation, the detection component 120 can includevisual detectors (e.g., a photoelectric detector). Visual detectors cancomprise a light source and a light sensor. The light source produces alight that is aimed at the light sensor. The light sensor can determinewhen the light is blocked. It is to be appreciated that the detectioncomponent can comprise one or more sensors. Further, the sensors cancomprise various sensors such as ionization sensors.

Detection component 120 converts the reactions of the sensory array orthe visual system into a digital signal. The digital signal represents achemical composition of the headspace. The memory 140 can store thedigital signal. The detection component 120 can compare the digitalsignal to various other digital signals stored in memory 140 todetermine an identity of a source associated with the headspace. In oneimplementation, detection component 120 uses at least one of a hashtable, fuzzy logic, artificial neural network (ANN), or patternrecognition modules, for example, to determine an identity of a sourceassociated with the headspace.

Now turning to FIG. 2 , there illustrated is a non-limiting exemplaryembodiment of a mobile device 200 capable of using input 224 to aid indetecting and/or identifying various odors, chemical compounds, aromas,and or gaseous substances. Mobile device 200 comprises a sample deliverycomponent 211, a detection component 220, an input component 226, acomputer processing unit (CPU) 230, an output component 250 and a memory240. Mobile device 200 provides for receiving a sample 206 and detectingor identifying a source 204 associated with sample 206. In one aspect,sample 206 is a portion of air in the proximity of mobile device 200. Inanother aspect, sample 206 can contain a scent, an odor, chemical(s),airborne particles, or gaseous substance(s).

In one aspect, CPU 230 is capable of executing various components and/orportions of components stored in a computer readable memory 240. Memory240 can also store a plurality of entries, each entry comprising adigital odor signals, class, and source name, for example. Each entrycan also comprise various other fields such as photo identification,date detected, and location, to name a few.

Sample deliver component 211 can actively or passively receive sample206. Detection component 220 can receive a headspace of sample 206 andanalyze the headspace. Detection component 220 can determine a digitalodor signal associated with the headspace.

Input component 226 can receive and analyze input 224. Input component226 can receive input 224 as audio, visual, text and/or other userinput. In one aspect, input component 226 includes one or more inputinterfaces such as a microphone, a camera, a key board, an actuator, atouch screen and/or other user interfaces capable of receiving input224, for example. In one aspect, input component 226 can receive input224 relating to source 204 and/or sample 206. For example, input 224 cancontain information relating to a source's class, image, and/orlocation.

In one implementation, input component 226 comprises a microphone. Inputcomponent 226 receives input 224 as audio information via themicrophone. Input component 226 can identify speech in input 224. Memory240 can store the digital signal. For example, a user can say “identifythis flower” and input component 226 can receive the audio as input 224.In one example, input component 226 can convert the audio to a digitalsignal and analyze the digital signal.

In another embodiment, input component 226 includes a user interfacedevice, such as a touch screen or keyboard, for example. In one aspect,the user input device can receive input 224 as text. In anotherimplementation, input 224 contains information relating to sample 206and/or source 204.

As another example, input component 226 can include a camera. The cameracan capture visual information. The visual information can be receivedby input component 226 as input 224. In one aspect, the visualinformation is an image of source 204. Input component 226 canidentification the image as relating to a class of objects, being aspecific object, and the like. In one implementation, input component226 determines if the image of source 204 is associated with an imagestored in memory 240. For example, an image is captured and inputcomponent 226 determines if the image is an image of a flower.

Detection component 220 receives analyzed input by input component 206.The analyzed input can contain information relating to source 204 and/orsample 206. Detection component 220 applies the analyzed input to narrowand/or improve identification of source 204 associated with sample 206.For example, detection component 220 receives analyzed input containinginformation such as “flower” and then detection component 220 cancompare the analyzed headspace to entries in memory 204 which have aclass type of “flower”. Detection component 220 can limit its comparisonof the digital headspace signal to entries in memory with a classassociation of “flower”.

In another aspect, detection component 220 can receive input 224 oranalyzed input from input component 206 which contains a plurality ofinformation relating to a source 204 and/or sample 206. For example,input 224 can contain a date field, a location field and an image field.In one aspect, input 224 can contain a date field and location field.Entries in memory 240 can have associated date ranges and locationranges. Detection component 220 can apply the input 224 to limitsearchable entries. For example, a flower may be indigenous to a certainlocation and may only bloom during a certain date range. Detectioncomponent 220 can apply input 224 to reduce the number of possibleentries.

Referring now to FIG. 3 , there illustrated is a non limiting exemplaryembodiment of a mobile device 300 in accordance with various aspects ofthis disclosure. Mobile device 300 comprises sample delivery component311, detection component 320, input component 326, processing unit 330,memory 340, and output component 350.

Mobile device 300 can receive a sample 306 associated with a source 304via a sample delivery component 311. Input component 326 can receive andanalyze input 324 containing information relating to sample 306 and/orsource 304. Detection component 320 can receive analyzed input and aheadspace of sample 306. Detection component 320 can analyze theheadspace in conjunction with the analyzed input.

In one aspect, processing unit 330 is capable of executing variouscomponents and/or portions of components stored in a computer readablememory 340. Memory 340 can also store a plurality of entries, each entrycomprising a digital odor signals, class, and source name, for example.Each entry can also comprise various other fields such as photoidentification, date detected, and location, to name a few.

In another aspect, mobile device 300 is in communication with one moreserver(s) 360. Communications can be facilitated via a wired (includingoptical fiber) and/or wireless technology. Server(s) 360 comprise one ormore server data store(s) that can be employed to store informationlocal to server(s) 360. In one implementation, server(s)'s 360 datastore(s) contains one or more entries, each entry relates to uniquesources with associated information, such as class, source name, digitalidentification, and image, for example.

In one implementation, detection component 320 receives entries and/orinformation relating to entries from server(s) 360. In another aspect,detection component 320 searches entries in server(s)'s 360 data store.

In another implementation, detection component 320 can send informationrelating to source 304 and or sample 306 to server(s) 360. Server(s) 360can record information in the server data stores.

Output component 350 can output information. In one embodiment, outputcomponent 350 includes one or more output devices such as a speaker,and/or display. Output component 350 outputs information relating tosample 306, source 304 and a detection result. A detection result caninclude information relating to source 304 such as a determined identityand/or class.

Referring now to FIG. 4 , there illustrated is sample deliver component400 which gathers a sample, delivers a sample, and/or removes a samplefrom a device in accordance with various aspects of this disclosure.Sample delivery component 400 can include am intake component 411, anintake line 414, an outtake line 422, an outtake component 430. Acontroller 450 can facilitate operation of sample delivery component 400and various other components in accordance with this disclosure, such asdetection component 440.

Intake component 440 gathers or receives a sample 460. In one aspect,intake component 440 passively receives sample 460 as sample 460diffuses through airspace. In another aspect, input component 440includes a mechanical device which can draw in sample 460. Themechanical device can include a bladed fan, a bladeless fan or otherknown devices capable of drawing in air as known in the field.

In another aspect, intake component 411 can comprise one or moreapertures in a mobile device. Sample 460 can enter the mobile devicethrough the one or more apertures.

Intake line 414 can transfer or provide a passage to various componentsin accordance with this disclosure, such as detection component 440, forexample. Intake line 414 can be in fluid communication with detectioncomponent 440, for example. Intake line 414 can comprise tubing, orother device of plastic, rubber, metal, or other suitable means as knownin the art. Detection component 440 can analyze sample 460 or aheadspace of sample 460.

Outtake line 422 can fluidly connect various components, such asdetection component 440, to outtake component 430. Outtake Air 470 canpass through outtake line 422 and exit the mobile device through outtakecomponent 430. Outtake component 430 can comprise one or more aperturesto allow the spent sample 460 or other outtake air 470 to exit themobile device.

In one aspect, outtake line 422 can comprise tubing, or other device ofplastic, rubber, polymer, ceramic, metal, or other suitable means asknown in the art.

In one implementation outtake component 430 can comprise a mechanicaldevice for drawing a sample. The mechanical device can include a bladedfan, a bladeless fan or other known devices (e.g., micro electromechanical systems (MEMS) devices) capable of drawing in air as known inthe field. For example, a system containing sensors and microjet MEMSactuators can be employed to exact some flow control, and synthetic jetscan be employed to reduce drag and modify flow over air foils and bluffbodies. In one aspect, outtake component 430 and intake component 411can each comprise one or more mechanical device. In anotherimplementation, intake component 411 or outtake component 430 canutilize the same one or more mechanical devices. In another aspect,outtake component 430 can include a mechanical device that causes air topass through input component 411 and output component 430.

In another implementation, outtake component 430 and intake component411 can both utilize the same one or more apertures to allow air toenter and exit a mobile device.

Referring now to FIG. 5 , there illustrated is a schematic diagram of anexemplary sample delivery component 500 in accordance with variousaspects of this disclosure. In accordance with various aspects of thisdisclosure, sample delivery component 500 can gather a sample in airspace, deliver the sample to various components in a mobile device, andremove the gathered sample from the mobile device.

Sample delivery component 500 can comprise one or more intake apertures511, fan 520, motor 524, intake duct 530, outtake duct 540, and one ormore outtake apertures 550. A controller 570 can control various aspectsof sample delivery component 500. Further, a power supply 560 can powervarious aspects of sample delivery component 500 such as fan 524, forexample.

A sample can be received through one or more intake apertures 511. Fan520 can draw in the sample. Likewise, motor 524 can receive power frompower supply 560. As fan 520 rotates, it creates a low pressure area inthe mobile device with respect to the airspace outside the device. Airis then caused to enter the one or more intake apertures 511.

The sample can pass through intake duct 530. Intake duct 530 can be incommunication with various components, such as detection component 536.The sample can also pass through or be forces through outtake duct 540.The spent sample can then exit through one or more outtake apertures550.

In other implementation, the intake duct 530 and outtake duct 540 can beof one unitary construction or modular construction. Likewise, powersupply 560 can be a battery, fuel cell or other power source. Powersupply 560 can be within sample delivery component 500 or can be a powersupply for a larger mobile device. In another aspect, the one or moreintake apertures 511 and one or more outtake apertures 550 can comprisethe same one or more outtake apertures.

Turning now to FIG. 6 , there illustrated is an exemplary schematicdiagram of a mobile device in accordance with this disclosure, as seenfrom a front view 600 and a back view 640. The mobile device includes adisplay 611, a microphone 620, a housing 630, a camera 650, a first atleast one opening 660 and a second at least one opening 670.

Housing 630 comprises a shell or enclosure that houses variouscomponents in accordance with the claimed subject matter. Housing 630can be made of a unitary or multi-piece construction and can consist ofone or more of metal, glass, plastic, ceramic, polymer, wood, and othermaterial known in the art.

In one aspect, display 611 can be a touch screen, monitor, digitaldisplay, and or other screen as known in the art. Display 611 canreceive input from a user in accordance with various aspects of thisspecification. For example, display 611 can receive input regarding asample of an odor, airborne gas or chemical and can receive commandsthrough user interaction.

In one implementation, microphone 620 can receive user input. Forexample, microphone 620 receives audio from a user such as “identifythis flower”. Various components in this disclosure can receive capturedinput, for example, an identification component can receive a capturedimage.

In another aspect, camera 650 can receive and or capture visual input.For example, camera 650 can be pointed at a source object. Camera 650can capture an image or images of the source object. Various componentsin this disclosure can receive captured input, for example, anidentification component can receive a audio input

In another aspect, the first at least one opening 660 can serve as anopening for a speaker, a heat ventilation and/or an intake for a sampledelivery component in accordance with various aspects of thisdisclosure. In one implementation, the first at least one opening 660comprises a plurality of slits, openings, or apertures in housing 630.

Similarly, the second at least one opening 670 can serve as an openingfor a speaker, a heat ventilation and/or an outtake for a sampledelivery component in accordance with various aspects of thisdisclosure. In one implementation, second at least one opening 670comprises a plurality of slits, openings, or apertures in housing 630.

In another implementation, the first at least one opening 660 and thesecond at least one opening 670 can comprise the same at least oneopenings. Thus, the amount of openings can be reduced.

Referring now to FIGS. 7-9 , there are illustrated methodologies and/orflow diagrams in accordance with the disclosed subject matter. Forsimplicity of explanation, the methodologies are depicted and describedas a series of acts. However, acts in accordance with this disclosurecan occur in various orders and/or concurrently, and with other acts notpresented and described herein. Furthermore, not all illustrated actsmay be required to implement the methodologies in accordance with thedisclosed subject matter. In addition, those skilled in the art willunderstand and appreciate that the methodologies could alternatively berepresented as a series of interrelated states via a state diagram orevents. Additionally, it should be further appreciated that themethodologies disclosed hereinafter and throughout this specificationare capable of being stored on an article of manufacture to facilitatetransporting and transferring such methodologies to computers. The termarticle of manufacture, as used herein, is intended to encompass acomputer program accessible from any computer readable device or storagemedium.

With reference to FIG. 7 , there is illustrated a methodology 700 fordetermining and/or identifying a source of a sample in accordance withvarious aspects of this disclosure. As an example, various mediaapplications, such as, but not limited to, mobile devices such as smartphones, tablets, PDA's, cooking utensils, and cookware can usemethodology 700. Specifically, methodology 700 receives a sample andidentifies the sample as associated with a source.

A mobile device can receive a sample via a sample delivery component at702, (e.g., sample delivery component 111). For example, a fan can causea sample to enter at least one aperture in a housing of a mobile device.In another example, a sample can passively enter at least one aperturein a housing of a mobile device at 702. As such, a mobile device cancontinuously monitor an airspace, such as to detect smoke or variouschemical compounds in an airspace.

At 704, a headspace of the sample can be analyzed by a detectioncomponent, for example. Analysis of a headspace can include a visualanalysis and/or a chemical analysis (e.g., via a sensory array).

At 706, an analyzed headspace can be compared with entries in a memory,such as memory 114. Comparison can comprise comparing substances and/orcompounds in the analyzed headspace with substances and/or compoundsassociated with entries in a memory.

At 708, the source associated with the headspace can be identified via adetection component, such as detection component 120. The analyzed andcompared headspace can be associated with a best matched entry or set ofentries. For example, a hash table analysis can result in one or moreentries being associated with the headspace.

At 711, the identified source can be output as a result via an outputcomponent, such as output component 250. The output result can include aname of a source or sources, images of a source or sources, and/oradditional associated information. The additional associated informationcan include genes, definition, common location, and the like.

Turning now to FIG. 8 , there is illustrated a methodology 800 fordetermining and/or identifying a source of a sample in accordance withvarious aspects of this disclosure. As an example, various mediaapplications, such as, but not limited to, mobile devices such as smartphones, tablets, PDA's, cooking utensils, and cookware can usemethodology 800. Specifically, methodology 800 receives a sample andidentifies the sample as associated with a source with use of additionalinput.

At 802, a sample is received via a sample delivery component (e.g.,sample delivery component 111). For example, a fan can cause a sample toenter at least one aperture in a housing of a mobile device. In anotherexample, a sample can passively enter at least one aperture in a housingof a mobile device at 802. As such, a mobile device can continuouslymonitor an airspace, such as to detect smoke or various chemicalcompounds in an airspace.

At 804, input is received and/or captured via one or more inputcomponent(s), such as display 611, a microphone 620, a housing 630,and/or a camera 650. Input can comprise multiple inputs such as but notlimited to user input, captured image, location information, dateinformation, and captured audio.

At 806, a headspace of the sample and input are analyzed by a detectioncomponent, such as detection component 120, for example. In one aspect,analysis of a headspace can include a visual analysis and/or a chemicalanalysis (e.g., via a sensory array). In another aspect, analysis ofinput can include audio analysis, text analysis, image analysis,location and date analysis, for example.

At 808, the analyzed headspace and the analyzed input are compared withentries in a memory, such as memory 114, for example. Comparison caninclude reducing possible sources to a set of possible sources viaanalyzed input, such as through a hash table, fuzzy logic and the like,via components executed by a CPU, such as CPU 130. In another aspect,the analyzed headspace can be compared to the reduced set of possiblesources.

At 811 a source or set of sources of the sample is determined, via adetection component, for example. In one aspect, the source or set ofsources can be associated with the analyzed sample and the analyzedinput. The association can be stored in memory, such as memory 114, forexample.

Turning now to FIG. 9 , there is illustrated a methodology 900 fordetermining and/or identifying a source of a sample in accordance withvarious aspects of this disclosure. As an example, various mediaapplications, such as, but not limited to, mobile devices such as smartphones, tablets, PDA's, cooking utensils, and cookware can usemethodology 900. Specifically, methodology 900 receives a sample andidentifies the sample as associated with an entry in a data store.

At 902, a headspace of a received sample is analyzed, (e.g. by detectioncomponent 111). Analysis of a headspace can include a visual analysisand/or a chemical analysis (e.g., via a sensory array).

At 904, can analyzed headspace can be compared with entries in a server,such as server 360. In one aspect, the server can comprise a memory. Thememory can contain a set of entries. Each entry of the set of entriescan comprise a number of fields, such as a source name, source id, daterange, location, genera, genus, class, image and the like.

At 906, a source can be determined as associated with the analyzedheadspace. In one aspect, a set of source can be determined as possiblesources associated with the analyzed headspace.

The systems and processes described below can be implemented withinhardware, such as a single integrated circuit (IC) chip, multiple ICs,an application specific integrated circuit (ASIC), or the like. Further,the order in which some or all of the process blocks appear in eachprocess should not be deemed limiting. Rather, it should be understoodthat some of the process blocks can be executed in a variety of ordersthat are not all of which may be explicitly illustrated herein.

FIG. 10 illustrates an embodiment of a mobile device 1000 (e.g.,personal digital assistants (PDAs), audio/video devices, mobile phones,MPEG-1 Audio Layer 3 (MP3) players, personal computers, laptops,tablets, etc.) that includes various optional components in connectionwith functionalities disclosed herein. The mobile device 1000 includes aprocessor 1001 and memory 1016. The components can be electricallyand/or communicatively coupled to one another to perform variousfunctions. An intake component 1002 collects a sample (e.g., air, gas,vapor, . . . ) in connection with electronic olfactory-basedidentification thereof. The intake component can passively collectsamples or actively (e.g., employment of a fan, suction, MEMs device,negative pressure, or any other suitable means for collection a sample).A set of sensors 1004 sense properties associated with the sample orinputs to the device 1000. The sensors 1004 can optionally include anyone or more of the following: chemical sensor 1006, image sensor 1008,olfactory sensor 1011, vibration sensor 1012, or touch sensor 1014. Itis to be appreciated that other suitable sensors can be employed inconnection with device 1000.

Search component 1020 can be employed to allow a user to search forinformation, e.g., via the Internet, to augment identification of asample. In an aspect, the search results can be ordered as a function ofrelevancy to the search criteria, relevancy to user preferences, orrankings associated with the search results. The search component 1020can be implemented on a manual basis (e.g., user input), or in anautomated manner. For example, the search component 1020 can regularlyor constantly run searches (e.g., in the background to generate contentthat is relevant to a user at a current point in time).

An input component 1022 can receive information about a source (e.g., ofa smell). A detection component 1026 can detect presence and amount ofchemicals in the headspace, e.g., collected by the sensors 1004. Thesensors 1004 can react to various chemicals within a headspace. Thereaction can cause a change in physical or electrical properties ofrespective sensors. In one example, absorption of the chemicals in theheadspace causes physical alterations of various sensors in the set ofsensors. Each sensor can react differently to the various chemicals. Theprocessor 1001 can transform the reactions of the sensory array into adigital signal. For example, the digital signal can be computed based ona statistical model. In one non-limiting embodiment, an organicultra-thin transistor chemical sensor having a channel that consists ofone or a few monolayers can be employed. The organic thin filmtransistor chemical sensors can have nearly monolayer thin film channelsthat act as highly-sensitive detectors of trace levels of organic vaporsand can perform quantitative vapor analysis. The organic ultra-thin filmcan be permeable to a chemical analyte of interest.

An inference component 1024 can infer actions or conclusions inconnection with identification of a source or compound associated with agather sample. As used herein, the term “inference” refers generally tothe process of reasoning about or inferring states of the system,environment, and/or user from a set of observations as captured viaevents and/or data. Inference can be employed to identify a specificcontext or action, or can generate a probability distribution overstates, for example. The inference can be probabilistic—that is, thecomputation of a probability distribution over states of interest basedon a consideration of data and events. Inference can also refer totechniques employed for composing higher-level events from a set ofevents and/or data. Such inference results in the construction of newevents or actions from a set of observed events and/or stored eventdata, whether or not the events are correlated in close temporalproximity, and whether the events and data come from one or severalevent and data sources. The inference component can perform autility-based analysis in connection with making an inference. Forexample, the cost of making an incorrect inference can be weighedagainst the benefit of making a correct inference.

Detection component 1026 can analyze chemical composition of a sample oranalyze a visual aspect of the sample. Pattern recognition component1028 can identify images captured by the device (e.g., via a cameracomponent). Audio recognition component 1030 can identify sources ofaudio received by the device. The device also includes a textrecognition component 1032. An analysis component 1034 analyzesinformation received from other components and can perform an analysisin connection with identifying source, smell, attribute, feature,composition, or the like associated with a sample.

Filtering component 1036 can employ and filter information to facilitatequickly converging on identification of source, smell, attribute,feature, composition, or the like in connection with a sample. Forexample, null items or features can be ruled out as potential candidatesin connection with determining identification. Input component 1038receives input, e.g., from a user. The input component 1038 can receivefor example, text, typed input, verbal or audio input, image input,gesture input, or any suitable type of input for inputting information.Output component 1040 outputs results of the analyses performed herein.Display component 1042 displays results of the analyses.

With reference to FIG. 11 , a suitable environment 1100 for implementingvarious aspects of the claimed subject matter includes a computer 1102.The computer 1102 includes a processing unit 1104, a system memory 1106,a codec 1105, and a system bus 1108. The system bus 1108 couples systemcomponents including, but not limited to, the system memory 1106 to theprocessing unit 1104. The processing unit 1104 can be any of variousavailable processors. Dual microprocessors and other multiprocessorarchitectures also can be employed as the processing unit 1104.

The system bus 1108 can be any of several types of bus structure(s)including the memory bus or memory controller, a peripheral bus orexternal bus, and/or a local bus using any variety of available busarchitectures including, but not limited to, Industrial StandardArchitecture (ISA), Micro-Channel Architecture (MSA), Extended ISA(EISA), Intelligent Drive Electronics (IDE), VESA Local Bus (VLB),Peripheral Component Interconnect (PCI), Card Bus, Universal Serial Bus(USB), Advanced Graphics Port (AGP), Personal Computer Memory CardInternational Association bus (PCMCIA), Firewire (IEEE 1394), and SmallComputer Systems Interface (SCSI).

The system memory 1106 includes volatile memory 1111 and non-volatilememory 1112. The basic input/output system (BIOS), containing the basicroutines to transfer information between elements within the computer1102, such as during start-up, is stored in non-volatile memory 1112. Byway of illustration, and not limitation, non-volatile memory 1112 caninclude read only memory (ROM), programmable ROM (PROM), electricallyprogrammable ROM (EPROM), electrically erasable programmable ROM(EEPROM), or flash memory. Volatile memory 1111 includes random accessmemory (RAM), which acts as external cache memory. According to presentaspects, the volatile memory may store the write operation retry logic(not shown in FIG. 11 ) and the like. By way of illustration and notlimitation, RAM is available in many forms such as static RAM (SRAM),dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM(DDR SDRAM), and enhanced SDRAM (ESDRAM).

Computer 1102 may also include removable/non-removable,volatile/non-volatile computer storage media. FIG. 11 illustrates, forexample, a disk storage 1114. Disk storage 1114 includes, but is notlimited to, devices like a magnetic disk drive, solid state disk (SSD)floppy disk drive, tape drive, Zip drive, LS-110 drive, flash memorycard, or memory stick. In addition, disk storage 1114 can includestorage media separately or in combination with other storage mediaincluding, but not limited to, an optical disk drive such as a compactdisk ROM device (CD-ROM), CD recordable drive (CD-R Drive), CDrewritable drive (CD-RW Drive) or a digital versatile disk ROM drive(DVD-ROM). To facilitate connection of the disk storage devices 1114 tothe system bus 1108, a removable or non-removable interface is typicallyused, such as interface 1116.

It is to be appreciated that FIG. 11 describes software, software inexecution, hardware, and/or software in combination with hardware thatacts as an intermediary between users and the basic computer resourcesdescribed in the suitable operating environment 1100. Such softwareincludes an operating system 1118. Operating system 1118, which can bestored on disk storage 1114, acts to control and allocate resources ofthe computer system 1102. Applications 1120 take advantage of themanagement of resources by operating system 1118 through program modules1124, and program data 1126, such as the boot/shutdown transaction tableand the like, stored either in system memory 1106 or on disk storage1114. It is to be appreciated that the claimed subject matter can beimplemented with various operating systems or combinations of operatingsystems. For example, applications 1120 and program data 1126 caninclude software implementing aspects of this disclosure.

A user enters commands or information into the computer 1102 throughinput device(s) 1128, non-limiting examples of which can include apointing device such as a mouse, trackball, stylus, touch pad, keyboard,microphone, joystick, game pad, satellite dish, scanner, TV tuner card,digital camera, digital video camera, electronic nose, web camera, andany other device that allows the user to interact with computer 11311.These and other input devices connect to the processing unit 1104through the system bus 1108 via interface port(s) 1130. Interfaceport(s) 1130 include, for example, a serial port, a parallel port, agame port, and a universal serial bus (USB). Output device(s) 1136 usesome of the same type of ports as input device(s) 1128. Thus, forexample, a USB port may be used to provide input to computer 1102, andto output information from computer 1102 to an output device 1136.Output adapter 1134 is provided to illustrate that there are some outputdevices 1136 like monitors, speakers, and printers, among other outputdevices 1136, which require special adapters. The output adapters 1134include, by way of illustration and not limitation, video and soundcards that provide a means of connection between the output device 1136and the system bus 1108. It should be noted that other devices and/orsystems of devices provide both input and output capabilities such asremote computer(s) 1138.

Computer 1102 can operate in a networked environment using logicalconnections to one or more remote computers, such as remote computer(s)1138. The remote computer(s) 1138 can be a personal computer, a server,a router, a network PC, a workstation, a microprocessor based appliance,a peer device, a smart phone, a tablet, or other network node, andtypically includes many of the elements described relative to computer1102. For purposes of brevity, only a memory storage device 1140 isillustrated with remote computer(s) 1138. Remote computer(s) 1138 islogically connected to computer 1102 through a network interface 1142and then connected via communication connection(s) 1144. Networkinterface 1142 encompasses wire and/or wireless communication networkssuch as local-area networks (LAN), wide-area networks (WAN), andcellular networks. LAN technologies include Fiber Distributed DataInterface (FDDI), Copper Distributed Data Interface (CDDI), Ethernet,Token Ring and the like. WAN technologies include, but are not limitedto, point-to-point links, circuit switching networks like IntegratedServices Digital Networks (ISDN) and variations thereon, packetswitching networks, and Digital Subscriber Lines (DSL).

Communication connection(s) 1144 refers to the hardware/softwareemployed to connect the network interface 1142 to the bus 1108. Whilecommunication connection 1144 is shown for illustrative clarity insidecomputer 1102, it can also be external to computer 1102. Thehardware/software necessary for connection to the network interface 1142includes, for exemplary purposes only, internal and externaltechnologies such as, modems including regular telephone grade modems,cable modems and DSL modems, ISDN adapters, wired and wireless Ethernetcards, hubs, and routers.

Referring now to FIG. 12 , there is illustrated a schematic blockdiagram of a computing environment 1200 in accordance with thisspecification. The system 1200 includes one or more client(s) 1202,(e.g., computers, smart phones, tablets, cameras, PDA's). The client(s)1202 can be hardware and/or software (e.g., threads, processes,computing devices). The client(s) 1202 can house cookie(s) and/orassociated contextual information by employing the specification, forexample.

The system 1200 also includes one or more server(s) 1204. The server(s)1204 can also be hardware or hardware in combination with software(e.g., threads, processes, computing devices). The servers 1204 canhouse threads to perform transformations of media items by employingaspects of this disclosure, for example. One possible communicationbetween a client 1202 and a server 1204 can be in the form of a datapacket adapted to be transmitted between two or more computer processeswherein data packets may include coded analyzed headspaces and/or input.The data packet can include a cookie and/or associated contextualinformation, for example. The system 1200 includes a communicationframework 1206 (e.g., a global communication network such as theInternet) that can be employed to facilitate communications between theclient(s) 1202 and the server(s) 1204.

Communications can be facilitated via a wired (including optical fiber)and/or wireless technology. The client(s) 1202 are operatively connectedto one or more client data store(s) 1208 that can be employed to storeinformation local to the client(s) 1202 (e.g., cookie(s) and/orassociated contextual information). Similarly, the server(s) 1204 areoperatively connected to one or more server data store(s) 1211 that canbe employed to store information local to the servers 1204.

In one exemplary implementation, a client 1202 can transfer an encodedfile, (e.g., encoded media item), to server 1204. Server 1204 can storethe file, decode the file, or transmit the file to another client 1202.It is to be appreciated, that a client 1202 can also transferuncompressed file to a server 1204 and server 1204 can compress the fileand/or transform the file in accordance with this disclosure. Likewise,server 1204 can encode information and transmit the information viacommunication framework 1206 to one or more clients 1202.

The illustrated aspects of the disclosure may also be practiced indistributed computing environments where certain tasks are performed byremote processing devices that are linked through a communicationsnetwork. In a distributed computing environment, program modules can belocated in both local and remote memory storage devices.

Moreover, it is to be appreciated that various components describedherein (e.g., detection components, input components, sample deliverycomponents, and the like) can include electrical circuit(s) that caninclude components and circuitry elements of suitable value in order toimplement the aspects of this innovation(s). Furthermore, it can beappreciated that many of the various components can be implemented onone or more integrated circuit (IC) chips. In one exemplaryimplementation, a set of components can be implemented in a single ICchip. In other exemplary implementations, one or more of respectivecomponents are fabricated or implemented on separate IC chips.

What has been described above includes examples of the implementationsof the present invention. It is, of course, not possible to describeevery conceivable combination of components or methodologies forpurposes of describing the claimed subject matter, but it is to beappreciated that many further combinations and permutations of thisinnovation are possible. Accordingly, the claimed subject matter isintended to embrace all such alterations, modifications, and variationsthat fall within the spirit and scope of the appended claims. Moreover,the above description of illustrated implementations of this disclosure,including what is described in the Abstract, is not intended to beexhaustive or to limit the disclosed implementations to the preciseforms disclosed. While specific implementations and examples aredescribed herein for illustrative purposes, various modifications arepossible that are considered within the scope of such implementationsand examples, as those skilled in the relevant art can recognize.

In particular and in regard to the various functions performed by theabove described components, devices, circuits, systems and the like, theterms used to describe such components are intended to correspond,unless otherwise indicated, to any component which performs thespecified function of the described component (e.g., a functionalequivalent), even though not structurally equivalent to the disclosedstructure, which performs the function in the herein illustratedexemplary aspects of the claimed subject matter. In this regard, it willalso be recognized that the innovation includes a system as well as acomputer-readable storage medium having computer-executable instructionsfor performing the acts and/or events of the various methods of theclaimed subject matter.

The aforementioned systems/circuits/modules have been described withrespect to interaction between several components/blocks. It can beappreciated that such systems/circuits and components/blocks can includethose components or specified sub-components, some of the specifiedcomponents or sub-components, and/or additional components, andaccording to various permutations and combinations of the foregoing.Sub-components can also be implemented as components communicativelycoupled to other components rather than included within parentcomponents (hierarchical). Additionally, it should be noted that one ormore components may be combined into a single component providingaggregate functionality or divided into several separate sub-components,and any one or more middle layers, such as a management layer, may beprovided to communicatively couple to such sub-components in order toprovide integrated functionality. Any components described herein mayalso interact with one or more other components not specificallydescribed herein but known by those of skill in the art.

Notwithstanding that the numerical ranges and parameters setting forththe broad scope of the invention are approximations, the numericalvalues set forth in the specific examples are reported as precisely aspossible. Any numerical value, however, inherently contains certainerrors necessarily resulting from the standard deviation found in theirrespective testing measurements. Moreover, all ranges disclosed hereinare to be understood to encompass any and all sub-ranges subsumedtherein. For example, a range of “less than or equal to 11” can includeany and all sub-ranges between (and including) the minimum value of zeroand the maximum value of 11, that is, any and all sub-ranges having aminimum value of equal to or greater than zero and a maximum value ofequal to or less than 11, e.g., 1 to 5. In certain cases, the numericalvalues as stated for the parameter can take on negative values.

In addition, while a particular feature of this innovation may have beendisclosed with respect to only one of several implementations, suchfeature may be combined with one or more other features of the otherimplementations as may be desired and advantageous for any given orparticular application. Furthermore, to the extent that the terms“includes,” “including,” “has,” “contains,” variants thereof, and othersimilar words are used in either the detailed description or the claims,these terms are intended to be inclusive in a manner similar to the term“comprising” as an open transition word without precluding anyadditional or other elements.

Reference throughout this specification to “one implementation,” or “animplementation,” means that a particular feature, structure, orcharacteristic described in connection with the implementation isincluded in at least one implementation. Thus, the appearances of thephrase “in one implementation,” or “in an implementation,” in variousplaces throughout this specification are not necessarily all referringto the same implementation. Furthermore, the particular features,structures, or characteristics may be combined in any suitable manner inone or more implementations.

Further, references throughout this specification to an “item,” or“file,” means that a particular structure, feature or object describedin connection with the implementations are not necessarily referring tothe same object. Furthermore, a “file” or “item” can refer to an objectof various formats.

As used in this application, the terms “component,” “module,” “system,”or the like are generally intended to refer to a computer-relatedentity, either hardware (e.g., a circuit), a combination of hardware andsoftware, or an entity related to an operational machine with one ormore specific functionalities. For example, a component may be, but isnot limited to being, a process running on a processor (e.g., digitalsignal processor), a processor, an object, an executable, a thread ofexecution, a program, and/or a computer. By way of illustration, both anapplication running on a controller and the controller can be acomponent. One or more components may reside within a process and/orthread of execution and a component may be localized on one computerand/or distributed between two or more computers. While separatecomponents are depicted in various implementations, it is to beappreciated that the components may be represented in one or more commoncomponent. Further, design of the various implementations can includedifferent component placements, component selections, etc., to achievean optimal performance. Further, a “device” can come in the form ofspecially designed hardware; generalized hardware made specialized bythe execution of software thereon that enables the hardware to performspecific function (e.g., media item aggregation); software stored on acomputer readable medium; or a combination thereof.

Moreover, the words “example” or “exemplary” are used herein to meanserving as an example, instance, or illustration. Any aspect or designdescribed herein as “exemplary” is not necessarily to be construed aspreferred or advantageous over other aspects or designs. Rather, use ofthe words “example” or “exemplary” is intended to present concepts in aconcrete fashion. As used in this application, the term “or” is intendedto mean an inclusive “or” rather than an exclusive “or”. That is, unlessspecified otherwise, or clear from context, “X employs A or B” isintended to mean any of the natural inclusive permutations. That is, ifX employs A; X employs B; or X employs both A and B, then “X employs Aor B” is satisfied under any of the foregoing instances. In addition,the articles “a” and “an” as used in this application and the appendedclaims should generally be construed to mean “one or more” unlessspecified otherwise or clear from context to be directed to a singularform.

What is claimed is:
 1. A mobile device comprising: a processor thatexecutes at least the following computer executable components stored ina non-transient computer readable storage medium: an electronicolfactory sensor that includes a nucleic acid-based sensor thatgenerates information regarding an airborne sample; a global positioningcomponent that receives information regarding location of the mobiledevice; an image capture device that captures an image of a visibleobject associated with the airborne sample; a detection component thatperforms analyses on the airborne sample, location of the mobile deviceand the visible object in the captured image; and a presentationcomponent that displays search results relating to identification of oneor more features associated with the airborne sample.